Prediction and Validation of Transcription Factors Modulating the Expression of Sestrin3 Gene Using an Integrated Computational and Experimental Approach

dc.contributor.authorSrivastava, Rajneesh
dc.contributor.authorZhang, Yang
dc.contributor.authorXiong, Xiwen
dc.contributor.authorZhang, Xiaoning
dc.contributor.authorPan, Xiaoyan
dc.contributor.authorDong, X. Charlie
dc.contributor.authorLiangpunsakul, Suthat
dc.contributor.authorJanga, Sarath Chandra
dc.contributor.departmentDepartment of BioHealth Informatics, IU School of Informatics and Computingen_US
dc.date.accessioned2017-06-08T13:31:01Z
dc.date.available2017-06-08T13:31:01Z
dc.date.issued2016-07-28
dc.description.abstractSESN3 has been implicated in multiple biological processes including protection against oxidative stress, regulation of glucose and lipid metabolism. However, little is known about the factors and mechanisms controlling its gene expression at the transcriptional level. We performed in silico phylogenetic footprinting analysis of 5 kb upstream regions of a diverse set of human SESN3 orthologs for the identification of high confidence conserved binding motifs (BMo). We further analyzed the predicted BMo by a motif comparison tool to identify the TFs likely to bind these discovered motifs. Predicted TFs were then integrated with experimentally known protein-protein interactions and experimentally validated to delineate the important transcriptional regulators of SESN3. Our study revealed high confidence set of BMos (integrated with DNase I hypersensitivity sites) in the upstream regulatory regions of SESN3 that could be bound by transcription factors from multiple families including FOXOs, SMADs, SOXs, TCFs and HNF4A. TF-TF network analysis established hubs of interaction that include SMAD3, TCF3, SMAD2, HDAC2, SOX2, TAL1 and TCF12 as well as the likely protein complexes formed between them. We show using ChIP-PCR as well as over-expression and knock out studies that FOXO3 and SOX2 transcriptionally regulate the expression of SESN3 gene. Our findings provide an important roadmap to further our understanding on the regulation of SESN3.en_US
dc.identifier.citationSrivastava, R., Zhang, Y., Xiong, X., Zhang, X., Pan, X., Dong, X. C., … Janga, S. C. (2016). Prediction and Validation of Transcription Factors Modulating the Expression of Sestrin3 Gene Using an Integrated Computational and Experimental Approach. PLoS ONE, 11(7), e0160228. http://doi.org/10.1371/journal.pone.0160228en_US
dc.identifier.urihttps://hdl.handle.net/1805/12908
dc.language.isoen_USen_US
dc.publisherPlosen_US
dc.relation.isversionof10.1371/journal.pone.0160228en_US
dc.relation.journalPLoS ONEen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/us
dc.sourcePMCen_US
dc.subjectSestrin3 Geneen_US
dc.subjectSESN3en_US
dc.subjectOxidative stressen_US
dc.subjectGlucose regulationen_US
dc.subjectLipid metabolismen_US
dc.subjectGene expressionen_US
dc.subjectBinding motifsen_US
dc.titlePrediction and Validation of Transcription Factors Modulating the Expression of Sestrin3 Gene Using an Integrated Computational and Experimental Approachen_US
dc.typeArticleen_US
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